Objective To systematically review the application and effectiveness of deep learning(DL)in diagnosis of mild cogni-tive impairment(MCI)among older adults.Methods PubMed,Web of Science,CNKI and Wanfang databases were searched for literatures related to the application of DL in MCI among older adults,from database inception to December,2024.A scoping review was conducted.The literature screening process followed the Scoping Review Report Specification list,and the quality assess-ment was conducted using the cross-sectional study quality evaluation tool developed by the Evidence-based Health Care Center.Results A total of eleven papers were included,from Italy,USA,South Korea,China,India and Switzerland,involving 11 829 elderly participants,publicated mainly between 2014 and 2024,reflecting the rapid development trend of the field in the last decade,which was in line with the timing of the development of DL technology.The quality scores of the included literatures were all six to seven.The types of studies were all cross-sectional studies with significant cross-disciplinary characteristics,mainly originating from the fields of clinical medicine,biology and neuroimaging.The literature data were mainly based on the Alzheimer's disease Neuroimaging Program database and integrated other data resources.In terms of data type,in addition to brain imaging data,one study based on text data was also included.In terms of models used,five of the studies were mainly based on convolutional neu-ral networks,and the rest used different DL modeling frameworks.The task types contained binary and triple classification.In terms of prediction results,the DL models constructed on multimodal data,such as brain imag-es,could be used to construct high-precision prediction models for MCI classification,and the models were all good,with accuracy more than 70%and AUC values more than 0.7.The diagnostic accuracy of some of the mod-els was more than 90%,and the model with the highest prediction accuracy was the one that used the Biceph-Net lightweight framework,with accuracy close to 100%,and the text analysis model based on Transformer made the AUC value of 0.846,which provided new ideas for the diagnosis of non-imaging data.Conclusion DL can not only provide strong support for the accurate identification of MCI in the elderly,but also provide auxiliary prediction tools for clinicians,which can help delay the progression of the disease and improve the prognosis of patients.

Objective To investigate the impact of virtual reality combined with body weight-supported treadmill training on phantom limb pain,lower limb dynamics,gait stability,balance func-tion,and quality of life in amputees.Methods A prospective study enrolled 100 unilateral lower limb amputees as participants,who were randomly divided into experimental group(n=50)and con-trol group(n=50).The experimental group received virtual reality combined with body weight-sup-ported treadmill training,while the control group received conventional rehabilitation training.Out-comes,including phantom limb pain intensity[Visual Analogue Scale(VAS),Douleur Neuropathique 4 Questions(DN4)scores],lower limb dynamics[vertical ground reaction force(Fz),anteroposterior ground reaction force(Fy),joint moments],gait parameters,static balance(Berg Balance Scale score),dynamic balance(stability time,proportion of gait support time),quality of life[12-Item Short-form Health Survey(SF-12)score],and activities of daily living[Modified Barthel Index(MBI)score]were assessed before intervention and at 4,8,and 12 weeks post-intervention.Results At 4,8,and 12 weeks post-intervention,the experimental group exhibited significantly lower VAS and DN4 scores compared to baseline and the control group(P＜0.05).Gait speed,stride length,ca-dence,stance time,Berg Balance Scale score,stability time,and proportion of gait support time improved in the experimental group compared to baseline and the control group(P＜0.05).SF-12 score,MBI score,peak Fz,peak Fy,knee flexion moment,ankle abduction moment,and stance phase proportion also increased significantly in the experimental group compared to baseline and the control group(P＜0.05).Conclusion Virtual reality combined with body weight-supported tread-mill training effectively alleviates phantom limb pain,improves lower limb dynamics,gait stability,and balance function,and enhances quality of life in amputees.

Objective::This study aimed to explore the causal link between olive intake and the occurrence of coronary heart disease (CHD) using Mendelian randomization (MR).Methods::In this study, genome-wide association study data from IEU OpenGWAS were employed. A 2-sample MR analysis was used to determine the causal association of olive intake with CHD and cardiovascular outcomes (myocardial infarction, heart failure, stroke, and death due to cardiac causes). The data for olive intake included 64,949 samples and 9,851,867 single nucleotide polymorphisms (SNPs), the data for CHD included 361,194 samples and 13,295,130 SNPs; The data for myocardial infarction included 361,194 samples and 12,640,541 SNPs, the heart failure include 208,178 samples and 16,380,422 SNPs, the data for stroke included 361,194 samples and 12,404,026 SNPs, and the data for death due to cardiac causes included 361,194 samples and 10,071,648 SNPs. Additionally, a 2-step, 2-sample MR approach was used for mediation analysis to determine whether lipid traits mediate the causal association between olive intake and CHD. The data for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, apolipoprotein B, and apolipoprotein A1 included 115,078 samples and 12,321,875 SNPs, while the data for triglycerides included 21,545 samples and 11,871,391 SNPs. Cochran’s Q test was applied to examine potential heterogeneity, and the MR-Egger method was used to assess horizontal pleiotropy among SNPs. Leave-one-out analysis was performed as a sensitivity analysis to evaluate the robustness of the results. Results::For each standard deviation increase in olive intake, the risk of CHD decreased by a substantial 1.9% (odds ratio (OR) = 0.981, 95% confidence interval (CI): 0.963 to 0.998, P = 0.031), the risk of myocardial infarction was significantly reduced by 1.6% (OR = 0.984, 95% CI: 0.969 to 0.999, P = 0.032), and the risk of heart failure declined by 62.1% (OR = 0.379, 95% CI: 0.192 to 0.746, P = 0.005). Furthermore, mediation analysis with MR indicated that lipid traits did not mediate the causal relationship between olive intake and CHD. Conclusion::There is a negative correlation between olive intake and the incidence of CHD, and this relationship is not mediated by lipid traits. Olive intake was also negatively associated with some cardiovascular outcomes, suggesting that increasing olive intake holds significant value in preventing the onset and progression of CHD.

Objective::This study aimed to explore the causal link between olive intake and the occurrence of coronary heart disease (CHD) using Mendelian randomization (MR).Methods::In this study, genome-wide association study data from IEU OpenGWAS were employed. A 2-sample MR analysis was used to determine the causal association of olive intake with CHD and cardiovascular outcomes (myocardial infarction, heart failure, stroke, and death due to cardiac causes). The data for olive intake included 64,949 samples and 9,851,867 single nucleotide polymorphisms (SNPs), the data for CHD included 361,194 samples and 13,295,130 SNPs; The data for myocardial infarction included 361,194 samples and 12,640,541 SNPs, the heart failure include 208,178 samples and 16,380,422 SNPs, the data for stroke included 361,194 samples and 12,404,026 SNPs, and the data for death due to cardiac causes included 361,194 samples and 10,071,648 SNPs. Additionally, a 2-step, 2-sample MR approach was used for mediation analysis to determine whether lipid traits mediate the causal association between olive intake and CHD. The data for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, apolipoprotein B, and apolipoprotein A1 included 115,078 samples and 12,321,875 SNPs, while the data for triglycerides included 21,545 samples and 11,871,391 SNPs. Cochran’s Q test was applied to examine potential heterogeneity, and the MR-Egger method was used to assess horizontal pleiotropy among SNPs. Leave-one-out analysis was performed as a sensitivity analysis to evaluate the robustness of the results. Results::For each standard deviation increase in olive intake, the risk of CHD decreased by a substantial 1.9% (odds ratio (OR) = 0.981, 95% confidence interval (CI): 0.963 to 0.998, P = 0.031), the risk of myocardial infarction was significantly reduced by 1.6% (OR = 0.984, 95% CI: 0.969 to 0.999, P = 0.032), and the risk of heart failure declined by 62.1% (OR = 0.379, 95% CI: 0.192 to 0.746, P = 0.005). Furthermore, mediation analysis with MR indicated that lipid traits did not mediate the causal relationship between olive intake and CHD. Conclusion::There is a negative correlation between olive intake and the incidence of CHD, and this relationship is not mediated by lipid traits. Olive intake was also negatively associated with some cardiovascular outcomes, suggesting that increasing olive intake holds significant value in preventing the onset and progression of CHD.

Objective To systematically review the application and effectiveness of deep learning(DL)in diagnosis of mild cogni-tive impairment(MCI)among older adults.Methods PubMed,Web of Science,CNKI and Wanfang databases were searched for literatures related to the application of DL in MCI among older adults,from database inception to December,2024.A scoping review was conducted.The literature screening process followed the Scoping Review Report Specification list,and the quality assess-ment was conducted using the cross-sectional study quality evaluation tool developed by the Evidence-based Health Care Center.Results A total of eleven papers were included,from Italy,USA,South Korea,China,India and Switzerland,involving 11 829 elderly participants,publicated mainly between 2014 and 2024,reflecting the rapid development trend of the field in the last decade,which was in line with the timing of the development of DL technology.The quality scores of the included literatures were all six to seven.The types of studies were all cross-sectional studies with significant cross-disciplinary characteristics,mainly originating from the fields of clinical medicine,biology and neuroimaging.The literature data were mainly based on the Alzheimer's disease Neuroimaging Program database and integrated other data resources.In terms of data type,in addition to brain imaging data,one study based on text data was also included.In terms of models used,five of the studies were mainly based on convolutional neu-ral networks,and the rest used different DL modeling frameworks.The task types contained binary and triple classification.In terms of prediction results,the DL models constructed on multimodal data,such as brain imag-es,could be used to construct high-precision prediction models for MCI classification,and the models were all good,with accuracy more than 70%and AUC values more than 0.7.The diagnostic accuracy of some of the mod-els was more than 90%,and the model with the highest prediction accuracy was the one that used the Biceph-Net lightweight framework,with accuracy close to 100%,and the text analysis model based on Transformer made the AUC value of 0.846,which provided new ideas for the diagnosis of non-imaging data.Conclusion DL can not only provide strong support for the accurate identification of MCI in the elderly,but also provide auxiliary prediction tools for clinicians,which can help delay the progression of the disease and improve the prognosis of patients.

Objective To analyze the prevalent characteristics,sequence type(ST),and blaOXA gene distribution of global Acineto-bacter pittii,and provide reference for prevention and clinical medication against this infection.Methods All the sequences of A.pittii genomes were downloaded in batch from NCBI by using Aspera software with deadline of November 30,2023,and perl script was used to extract the meta information of strains in batch from the downloaded GBK file.A self-made Perl program was utilized to extract the nucleotide coding sequence of the gene from each genome sequence file of A.pittii as the analysis database.BLASTN comparative analy-sis was implemented by using the allelic sequences of 7 housekeeping genes of the genus Acinetobacter Sp downloaded from the website as a query database to determine the ST of each genome.The nucleotide sequences of the blaOXA genes were downloaded from the NCBI pathogen resistance gene database and the self-written AMRG software was utilized to analyze the distribution of blaOXA gene among A.pittii.Results A total of 305 A.pittii genomes were obtained,which were mainly isolated from 1990 to 2020.The isolation rates showed an increasing trend of year by year with the highest isolation rate in 2015.The separation rates of the United States,China and Germany ranked in the top three positions,with the separation rates of 29.5％(90 strains),15.7％(48 strains),and 13.4％(41 strains),respectively.A total of 180(59.0％)specimens were sourced from humans,of which 42(23.3％)were from sputum,27(15.0％)from blood,and 15(8.3％)from skin and soft tissues.The 305 strains of A.pittii were assigned into 79 STs,among which ST93(14.4％),ST64(12.1％)and ST63(11.8％)accounted for the highest proportion.In the United States,China and Germany,the infections were mainly affected by ST64,ST63 and ST93,respectively.The 305 A.pitti carried the blaOXA gene except 6 strains,while the remained 299 strains carried 31 blaOXA variants,of which,252 blaOXA genes were found to own the carbapenemase hydrolysis activity and 146 strains carried blaOXA-500 gene.Conclusion There should be regional differences in the global distribution of A.pittii,and the high prevalence of the carbapenemase gene blaOXA suggested a potential trend of multi-drug resistance,which is worthy to be monitored.

Objective To develop a deep learning method for volumetric assessment of traumatic intracerebral hemorrhage(TICH)using the Trans-UNet model and to compare its performance with traditional formula-based methods.Methods CT data from 141 TICH patients admitted to Army Medical Center of PLA between May 2018 and May 2023 were collected.A deep learning method based on the Trans-UNet model was established.Manual delineation via picture archiving and communication system(PACS)was served as the gold standard for comparing the accuracy,consistency,and time efficiency of our method against 10 different formula-based methods for measuring the amount of TICH.Results The median volume of TICH,as manual delineation via PACS,was 1.167 mL,with a median measurement time of 135 s per patient.The median percentage error in volume between the deep learning method and manual delineation via PACS was 3.59％.Spearman correlation coefficient was 0.999(P＜0.001),and a median measurement time was only 4.38 s per patient.In contrast,in the formula-based methods,the lowest median percentage error in volume was 16.451％,the highest Spearman correlation coefficient was 0.986(P＜0.001),and the lowest median measurement time was 20 s for a single patient.The statistical differences were observed in percentage error in volume and measurement time between the 2 types of methods(all P＜0.001).Conclusion Our developed deep learning method for volumetric assessment of TICH is superior to the formula-based methods in terms of measurement accuracy and time efficiency.

Myocardial infarction(MI)is an irreversible myocardial injury caused by continuous ische-mia and hypoxia of coronary arteries,which seriously threatens people's life and health.Exosomes are nanoscale bilayer lipid vesicles released into the surrounding body fluids after the fusion of multivesicular bodies and plasma membranes.As an important bioactive molecule contained in exosomes,miRNAs regulate the pathological mechanism of MI by changing various biological pathways.Exosomes have the advantages of high stability,low toxicity,and controllable dose.Exosome-based cell-free therapy loaded with miRNA has e-merged.This article reviewed the diagnostic and prognostic value of exosome miRNA in MI,and discussed the application prospects and limitations of exosomal cell-free therapy.

Non-exosomal non-coding RNAs (non-exo-ncRNAs) and exosomal ncRNAs (exo-ncRNAs) have been associated with the pathological development of myocardial infarction (MI). Accordingly, this analytical review provides an overview of current MI studies on the role of plasma non-exo/exo-ncRNAs. We summarize the features and crucial roles of ncRNAs and reveal their novel biological correlations via bioinformatics analysis. The following contributions are made: (1) we comprehensively describe the expression profile, competing endogenous RNA (ceRNA) network, and "pre-necrotic" biomarkers of non-exo/exo-ncRNAs for MI; (2) functional enrichment analysis indicates that the target genes of ncRNAs are enriched in the regulation of apoptotic signaling pathway and cellular response to chemical stress, etc.; (3) we propose an updated and comprehensive view on the mechanisms, pathophysiology, and biomarker roles of non-exo/exo-ncRNAs in MI, thereby providing a theoretical basis for the clinical management of MI.
Humans ; RNA, Untranslated/genetics* ; RNA ; Myocardial Infarction/genetics* ; Biomarkers ; Computational Biology ; MicroRNAs/genetics*

Objective To study the characteristics of a rat model of migraine with hyperactivity of liver-yang and blood stagnation,which was established by Fuzi Decoction combined with electrical stimulation of the trigeminal ganglion.Methods The 30 SD rats were divided into normal group,model group,and Zhengtian pill group(1.6 g·kg-1),with 10 rats in each group.Rats in the model group and Zhengtian pill group were fed with aconite decoction(2.00 g·kg-1)once a day for 28 day to establish the hyperthermia model;On the 15 day of intragastric administration,rats in the Zhengtai pill group were simultaneously given Zhengtai pill solution once a day for 14 day;At 29 day,the trigeminal ganglion was stimulated to create the migraine model of hyperliver and stasis.After 30 min of the last dose,the macroscopic signs and behaviors were observed,and the blood rheology was detected by blood visticometer.Positive substance P(SP)expression,mRNA and relative protein expression in the trigeminal cervical pulp complex(TCC)in rat mice by immunohistochemistry,RT-qPCR and Western blot analysis.Results Compared with the normal group,the model group has macro signs such as red eyes,irritability,cage fighting,dark tongue and stasis points;regular head positioning and frequent hair management;increased distance in the central area(P<0.05).The relative viscosity of whole blood,plasma viscosity,red blood cell aggregation index all increased(P<0.05),and the red blood cell variant index decreased(P<0.05);SP positive expression,mRNA and the relative protein expression increased in TCC(P<0.05).Compared with model group,Zhengtian pill group can improve macro representation and behavior significantly;can significantly reduce central distance(P<0.05);can reduce plasma viscosity,high-shear relative viscosity of whole blood,and red blood cell aggregation index(P<0.05);increase the Red blood cell variant index significantly(P<0.05);down-regulate SP positive expression,mRNA and relative protein expression in TCC(P<0.05,P<0.01).Conclusion SD rats were used for 4 weeks to construct a migraine model of hyperhepatic hyperactivity and stasis,which was basically consistent with the clinical manifestations.